No abstract

To preemptively respond to urban flood disasters, a flood prediction system that provides a connection service with a smart city data hub was developed. The systems developed in this study provide real-time and predicted rainfall data, 1D and 2D flood prediction data, manhole-based flood prediction and warning information, and flood vulnerability index by administrative district. A one-dimensional analysis for the water depth and overflow amount of each manhole was calculated using the Storm Water Management Model (SWMM). A two-dimensional inundation analysis, the Two-Dimensional Inundation System (2DIS), which is capable of two-dimensional surface inundation analysis, was applied. The model can simulate surface flooding using the manhole overflow rate of the SWMM model. In the system, the flood prediction information was made based on the rainfall scenario, and the applied rainfall is 30-90 mm per hour, while the rainfall time distribution is Huff 3rd quartile. The propagation of flood conditions in the system can provide a five-stage (Safety, Attention, Caution, Alert, and Serious) scale depending on the water depth and surcharge conditions of the pipeline. The flood prediction model developed in this study was compared and verified with the existing flood survey data in the Dalseo Drainage Basin in 2002, and the model verification showed that the probability of flood detection (POD) was more than 80%.